# Mem0 vs Mastra: Which AI Memory Platform Is Better for Production Agents? If you are looking for a Mastra alternative focused on production AI agent memory, Mem0 is built for persistent memory across users, sessions, agents, and organizations, with published benchmark results, under 7K tokens per retrieval, and enterprise-grade compliance out of the box. Mastra's Observational Memory (OM) posts strong LongMemEval scores — but those scores use newer, more expensive models, and Mastra has not published LoCoMo or BEAM results. Mem0 leads on token efficiency, memory scopes, language support, and enterprise compliance. Published Date: Jul 8, 2026 Open source Managed cloud Free Tier PRICING self hosting LongMemEval LoCoMo BEAM 1M / 10M Compliance Language Support Memory scopes Primary Purpose Local / MCP support ~ Tokens / Retrieval | Feature | Mem0 | Mastra | |-------------------------------------|-----------------------------|-----------------------------| | Pricing | Starting from $19/month | Not published | | LongMemEval | 94.4 | 94.8 | | LoCoMo | 92.5 | ~ | | BEAM 1M / 10M | 64.1 / 48.6 | Intentionally not published | | Compliance | SOC 2 (Type 1), HIPAA | Not published | | Language Support | Python & TypeScript | TypeScript only | | Memory scopes | Session, User, Agent, Org | Thread / resource scoped | | Primary Purpose | Dedicated agent memory layer | TypeScript agent orchestration framework | | ~ Tokens / Retrieval | <7K (on BEAM 10M) | ~30K avg context window | ## Benchmarks Mem0’s token-efficient memory algorithm leads across three major memory evaluations: LongMemEval, LoCoMo, and BEAM. The key difference is not only accuracy, but accuracy under a practical token budget. #### LongMemEval Long-horizon recall and temporal reasoning across multi-session chat. **MEM0** **94.4** **6.7K Tokens** **Mastra** **94.8** **~30K Tokens** #### LoCoMo Naturalistic long conversation memory across sessions and question categories. **MEM0** **92.5** **Mastra** **~** ### Why Mem0 Wins for Production Agent Memory Mem0 is stronger when your core problem is accurate, persistent memory for AI agents in production. ## Mem0 wins on production agent memory **Choose Mem0 when you need accurate, token-efficient, real-time agent memory with a production-grade managed platform.** **Choose Mem0 if:** - You need a memory layer with strong benchmark results on both LongMemEval and LoCoMo - You want production memory across Session, User, Agent, and Org rather than thread-scoped storage - You need token-efficient retrieval — under 7K tokens vs Mastra OM's ~30K context window - You need enterprise readiness, including SOC 2 and HIPAA support **CHOOSE Mastra IF:** - You are comfortable with Mastra's memory abstractions and stable-context-window approach - You want TypeScript-native agent orchestration with workflows, tool-calling, and built-in observability - You are building entirely within the Mastra ecosystem and don't need cross-framework memory ## For developers who want proof, not promises. **80K users** #### “Mem0 transformed our AI companion in just one day of integration, delivering personalized support that remembers user journeys and significantly reduced our costs. It's been one of our highest-ROI decisions.” Koby Conrad CEO, Sunflower #### Mem0 allowed us to unlock true personalized tutoring for every student, and it took us just a weekend to integrate. Michael Tong CTO, RevisionDojo **Weekend integration** #### Mem0 turned our AI tutors into true learning companions - tracking each student’s struggles, strengths, and learning style across the entire platform and tools. Abhi Arya Co-Founder, Opennote **40% token reduction** ## Install In Minutes **Integrate Mem0 in a few lines of code with Python and JavaScript SDKs plus REST, so you ship memory without touching infra.** **Python** **node js** ```python 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 # Step 1 — Install the SDK (run in your terminal, not in Python):#pip install mem0ai # Step 2 — Save this as mem0_quickstart.py and run with: python mem0_quickstart.pyimport osfrom mem0 import MemoryClient # Set your API key (get one at https://app.mem0.ai)client = MemoryClient(api_key=os.getenv("MEM0_API_KEY", "your-api-key-here")) # Add a memorymessages = [ {"role": "user", "content": "I'm a vegetarian and allergic to nuts."}, {"role": "assistant", "content": "Got it! I'll remember your dietary preferences."},]client.add(messages, user_id="user123") # Search memoriesresults = client.search( "What are my dietary restrictions?", user_id="user123",)print(results) ``` ## AI memory that adapts to your domain Mem0 helps AI remember what matters. **Healthcare** **Education** **E-commerce** **Customer Support** **Sales & CRM** #### Smart Patient Care Assistant Remembers patient history, allergies, and treatment preferences across visits therefore providing personalized care that improves with every interaction. #### Chronic Condition Companion Learns what works (and what doesn’t) for the patient over time, offering thoughtful reminders and insights tailored to each patient’s journey. #### Therapy Progress Tracker Builds on previous sessions to deliver consistent, context-aware mental health support. Creates trust through conversations that remember what matters to each patient. ## Built for enterprise Designed for control Memory at scale is infrastructure. Mem0 gives enterprise teams governance, reliability, and full observability so engineers spend time building, not recovering lost context. #### Governance SOC 2, HIPAA, BYOK, zero-trust. Your data stays yours. #### Portable Kubernetes, private cloud, or air-gapped. Same API everywhere. #### Auditable Every read and write logged. Know what, who, and when. We take security and privacy seriously. Mem0 is SOC 2 (Type 1) and HIPAA compliant, ensuring your data is protected with industry-standard safeguards at every step. ### FAQ ## Frequently Asked Questions - **Is Mem0 better than Mastra?** - **How does Mem0's algorithm work?** - **Does Mastra have enterprise compliance like SOC 2 or HIPAA?** - **Can I use Mem0 inside a Mastra agent?** - **How do I get started with Mem0?**